Senior Staff Scientist, Data Science (Computational Biology & AI)

Thermo Fisher ScientificSan Jose, CA
Hybrid

About The Position

As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer. DESCRIPTION: Join our team as a Senior Staff Scientist in Data Science (Computational Biology & AI), where you will drive innovation at the intersection of machine learning and life sciences. In this role, you will develop advanced computational and statistical methods to analyze large-scale biological datasets, enabling breakthroughs in proteomics, multi-omics, and translational research. You will design and implement AI-driven models and data analysis workflows for complex biological systems, working closely with cross-functional teams of biologists, clinicians, and data scientists. This position offers the opportunity to contribute to high-impact scientific research, develop novel methodologies, and translate cutting-edge analytics into real-world scientific and clinical applications.

Requirements

  • Ph.D. in Applied Mathematics, Computational Biology, Bioinformatics, Computer Science, or related field
  • 10+ years of experience in computational biology, bioinformatics, or data science in academia or industry
  • Proven track record of leading data analysis in large-scale, multi-omics or proteomics projects
  • Strong expertise in machine learning and statistical modeling, including deep learning (e.g., PyTorch) and Bayesian methods
  • Advanced programming skills in Python, R, and/or Julia, with experience in scientific computing and data analysis
  • Experience with large-scale biological data analysis, including proteomics, interactomics, or genomics datasets
  • Hands-on experience with cloud and high-performance computing environments (e.g., AWS, SLURM, Docker)
  • Strong knowledge of data integration, statistical inference, and multi-modal data analysis
  • Familiarity with SQL and database systems (PostgreSQL, MySQL, etc.)
  • Deep understanding of molecular biology, proteomics, or systems biology
  • Experience developing novel computational methods for emerging biological assays or experimental platforms
  • Track record of scientific publications in high-impact journals and contribution to scientific communities

Nice To Haves

  • Experience with multi-omics integration and cohort-scale data analysis
  • Background in developing reusable data analysis frameworks or open-source contributions
  • Experience supporting customer-facing scientific applications or consulting on data analysis strategies

Responsibilities

  • Develop advanced computational and statistical methods to analyze large-scale biological datasets, enabling breakthroughs in proteomics, multi-omics, and translational research.
  • Design and implement AI-driven models and data analysis workflows for complex biological systems.
  • Work closely with cross-functional teams of biologists, clinicians, and data scientists.
  • Contribute to high-impact scientific research.
  • Develop novel methodologies.
  • Translate cutting-edge analytics into real-world scientific and clinical applications.
  • Lead projects and mentor scientists or data scientists.
  • Define and communicate data science strategy to technical and non-technical stakeholders.
  • Collaborate across interdisciplinary teams (biology, engineering, data science).

Benefits

  • A choice of national medical and dental plans, and a national vision plan, including health incentive programs
  • Employee assistance and family support programs, including commuter benefits and tuition reimbursement
  • At least 120 hours paid time off (PTO)
  • 10 paid holidays annually
  • Paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave)
  • Accident and life insurance
  • Short- and long-term disability
  • Competitive 401(k) U.S. retirement savings plan
  • Employees’ Stock Purchase Plan (ESPP)
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